The Economics of Climate Change and Adaptation

1. The Economics of Climate Change and Adaptation Speaker: Jean-Marc Mayotte MA Water Resources Engineering University of Colorado and University of Copenhagen CIEM DANIDA Project

2. Talking Points What is a GCM? Accounting for future climate uncertainty Linking climate to the economy Data needs Example: Mozambique Concluding remarks EMPHASIZE that this is only covering the climate change portion and the inputs to the CGE. The CGE will not be discussed Many of the slides herein are the previous work of Dr. Ken Strzepek of the University of ColoradoEMPHASIZE that this is only covering the climate change portion and the inputs to the CGE. The CGE will not be discussed Many of the slides herein are the previous work of Dr. Ken Strzepek of the University of Colorado

3. General Circulation Model A mathematical representation of the general circulation of the planetary atmosphere based on the Navier-Stokes equations There are 22 GCMs officially recognized by the International Panel on Climate Change Predictions of future climate are based on CO2 emission scenarios used to estimate the concentration of CO2 in the Earth�s atmosphere Grid resolution varies from 100m to 5000m Grid resolution varies from 100m to 5000m

4. Future Climate is UncertainEconomic and Model Uncertainty Note the deviation at 2050. All models predict a higher level of uncertainty past 2050. Note the �gray area� representing the �envelope� of potential futures. This is very important to the modeling concept. We want to insure that we are capturing the extreme possibilities. Note the deviation at 2050. All models predict a higher level of uncertainty past 2050. Note the �gray area� representing the �envelope� of potential futures. This is very important to the modeling concept. We want to insure that we are capturing the extreme possibilities.

5. Wide Variation at Local Scale between Models NOTE: The spatial differences between model predictions. This is prevalent in all models used and needs to be taken into account when predicting climate futures. Spatial differences in climate are just as important as temporal differences (maybe more so) NOTE: The spatial differences between model predictions. This is prevalent in all models used and needs to be taken into account when predicting climate futures. Spatial differences in climate are just as important as temporal differences (maybe more so)

6. Observed & Predicated Trends Precipitation intensity is predicted to increase on average for all scenarios, mostly in the mid-latitudes The number of dry days is also predicted to vary greatly with the highest deviation in the lower latitudes.Precipitation intensity is predicted to increase on average for all scenarios, mostly in the mid-latitudes The number of dry days is also predicted to vary greatly with the highest deviation in the lower latitudes.

7. Consistent Message from GCMs Change in Daily Precipitation Intensity Change in inter-storm arrival Seasonal & Spatial Variation This means that historic information cannot be used to plan for future events. Planning infrastructure requires a different outlook. Introduce the concept of linking all of this to the economy and the importance of accounting for all believed climate scenarios. This means that historic information cannot be used to plan for future events. Planning infrastructure requires a different outlook. Introduce the concept of linking all of this to the economy and the importance of accounting for all believed climate scenarios.

8. Selecting the Climate Change Scenarios Not all GCMs are used in the analysis Models are picked based on their predicted Climate Moisture Index (CMI) Simple water balance that accounts for both precipitation and evaporation The average CMI for the time-horizon (2000 � 2100) is predicted using each GCM. The models that predict the �wettest� and the �driest� CMI in the region considered are used in an effort to capture the �wettest� (+1) and �driest� (-1) possible futures Emphasize that this is much of the work. Correctly choosing climate scenarios means analysis is efficient and comprehensiveEmphasize that this is much of the work. Correctly choosing climate scenarios means analysis is efficient and comprehensive

9. Climate Moisture Index (CMI) Note that all countries have a CMI less than 1 World Bank regions: Africa East Asia and the Pacific Europe and Central Asia Latin America and the Caribbean Middle East and North Africa South Asia Note that all countries have a CMI less than 1 World Bank regions: Africa East Asia and the Pacific Europe and Central Asia Latin America and the Caribbean Middle East and North Africa South Asia

10. Adapt to what? � Global Wet and Dry Again, note the spatial differences b/w modelsAgain, note the spatial differences b/w models

12. Uses of History Simulations are based on historical experience The impacts from future CC will likely resemble those from the current climate but with some modifications to their frequency, timing, and magnitude These changes in the distribution require a new approach to �risk based� design (i.e. what used to be a 1/50 year storm may become a 1/25 year storm) Models The models used to relate CC to the economy are constructed based on underlying science and knowledge of technology/biology and tested, calibrated, and legitimized using historic climate data Suite of statistical techniques used to generate future climate scenarios such that they are not entirely uncharacteristic of past events but exhibit appropriate changesSuite of statistical techniques used to generate future climate scenarios such that they are not entirely uncharacteristic of past events but exhibit appropriate changes

13. Extensive Data Needs The analysis is spatially and temporally dependant and the quality of its outputs are entirely reliant on the quality of its input data Many global databases are available but locally collected and quality assured data increases the applicability and reliability of model outputs

14. Data Needs Climatologic data Precipitation, min/max temperature, pressure, humidity Land cover and vegetation data Wetlands Agricultural land Commercial Residential Industrial Institutional DEM (Digital Elevation Map) data 10-30 m preferred Soil Slope Hydraulic conductivity Population Density maps Poverty maps Housing type Infrastructure Road inventory maps Bridge inventory Rail inventory Urban drainage Property value Hydropower production By province Tropical Storms/Cyclones Storm track Magnitude Rainfall Wind speed Storm surge Economic Data Manufacturing production values Crop production

16. The Economics of the Adaptation to Climate Change (EACC) Mozambique Massachusetts Institute of Technology (MIT), University of Colorado, and University of Copenhagen Funded by the World Bank

17. How are Mozambique and Vietnam Similar? Both are estuary countries and are strongly reliant on coastal infrastructure making them very vulnerable to sea level rise Both have a large discrepancy between the rich and poor Both exhibit rather significant economic growth and development but have done little to adapt to potential changes in climate Agriculture is a very significant part of both economies and are very reliant on available surface water

18. Adapt to what? Mozambique Wet and Dry Precipitation in 2050

19. Adapt to what?Mozambique Wet and Dry Temperature in 2050

20. EACC Mozambique Modeling Framework

21. Agriculture Effects on yield in 2050 compared to historic averages

22. Roads Cost of Maintaining Existing Road Inventory 2010 - 2050

23. Hydropower Annual Generation 2005 - 2050 Potential energy deficit due to climate change relative to BASE generation potential (2005 � 2050):

24. Impact on Coastal Zones, 2010 � 2050 Extracted from Global Study Specific to Mozambique

25. Summary of CGE Modeling Results Without public policy changes, the worst scenario results in a net present value of damages of nearly US$7 billion. equivalent to an annual payment of US$390 million (5% discount rate). Hardening rural roads reduces worst case impacts substantially, restoring approximately 1/3 of lost absorption. Remaining welfare losses could be regained with improved agricultural productivity or human capital accumulation. Investments costs required to restore welfare losses are subject to debate, but are reasonably less than US$390 million per year over 40 years.

26. Conclusion It is our hope that we will be able to produce similar results for Vietnam as has been done for Mozambique The ultimate goal is to find adaptation options that are of �no regret�, or infrastructure and investment that would benefit the people and economy regardless of potential climate changes It is our thought that developing whilst adapting to climate change is essential to insuring continued economic growth

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